Understanding the trends and periodicities in geophysical processes is imperative for assessing and forecasting their future change. However, it is possible to mistreat parts of cycles as linear trends with sudden breaks when analysing short-term data. We demonstrate this through the analysis of solar irradiance data as well as Northern Hemisphere (NH) and Southern Hemisphere (SH) sea surface temperature (SST) data sets, with emphasis on the (a) analyses of trends in total solar irradiance (TSI) and (b) association of trends in SST with solar activity during the period from 1900 to 2017. The trends estimated using singular spectrum analysis together with linear regression revealed statistically significant long periodic non-linear trends in both TSI and SST data. Our results suggest that the appraisal of linear trends to identify their breaks/sudden changes is a biased approach when analysing data sets of shorter periods, when the data are governed by long periodic dynamical processes. The non-linear trends identified in SST data may be physically associated with the TSI trend change and anthropogenic CO2. A plausible physical mechanism is also discussed with respect to the influence of solar activity on the trend in atmospheric CO2. Finally, our study concludes that (1) breaks in linear trends are pseudo-attribution of parts of cycles, and (2) the statistically significant trends in NH and SH SST are mainly associated with loadings from trend changes in solar irradiance.

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线性趋势或周期的一部分中断？

了解地球物理过程的趋势和周期性对于评估和预测其未来变化至关重要。但是，在分析短期数据时，可能会将部分周期误认为是具有突然中断的线性趋势。我们通过分析太阳辐照度数据以及北半球 (NH) 和南半球 (SH) 海面温度 (SST) 数据集来证明这一点，重点是 (a) 总太阳辐照度 (TSI) 趋势分析(b) 1900 年至 2017 年期间 SST 趋势与太阳活动的关联。使用奇异光谱分析和线性回归估计的趋势揭示了 TSI 和 SST 数据中具有统计意义的长周期非线性趋势。我们的结果表明，在分析较短周期的数据集时，当数据受长周期动态过程控制时，评估线性趋势以识别其中断/突然变化是一种有偏见的方法。SST 数据中确定的非线性趋势可能与 TSI 趋势变化和人为 CO2 物理相关。还讨论了关于太阳活动对大气 CO2 趋势影响的合理物理机制。最后，我们的研究得出结论：（1）线性趋势的中断是周期部分的伪归因，（2）NH 和 SH SST 的统计显着趋势主要与太阳辐照度趋势变化的载荷有关。当数据受长周期动态过程控制时。SST 数据中确定的非线性趋势可能与 TSI 趋势变化和人为 CO2 物理相关。还讨论了关于太阳活动对大气 CO2 趋势影响的合理物理机制。最后，我们的研究得出结论：（1）线性趋势的中断是周期部分的伪归因，（2）NH 和 SH SST 的统计显着趋势主要与太阳辐照度趋势变化的载荷有关。当数据受长周期动态过程控制时。SST 数据中确定的非线性趋势可能与 TSI 趋势变化和人为 CO2 物理相关。还讨论了关于太阳活动对大气 CO2 趋势影响的合理物理机制。最后，我们的研究得出结论：（1）线性趋势的中断是周期部分的伪归因，（2）NH 和 SH SST 的统计显着趋势主要与太阳辐照度趋势变化的载荷有关。